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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： T. Biatek W. Hamidouche J.-F. Travers O. Deforges IRT b <> com Cesson-Sevigne France IETR/ INSA de Rennes Rennes France TDF Cesson-Sevigne France

ISBN: (纸本)9781479999897

Scalable video coding consists in compressing the video sequence into a layered bitstream where each layer refers to different spatial, temporal or quality representation of the video. Scalability enables compression gain compared to the simulcast encoding of layers thanks to inter-layer predictions. The scalable HEVC extension (SHVC) is the latest scalable technology promising up to 30% bitrate gains under the common test conditions, defined by JCT-VC. These conditions do not consider UHD and use fixed quantization step, which is not relevant in operational environment. In this paper, we propose an innovative adaptive rate control algorithm for SHVC. We consider HD as a base layer and UHD as an enhancement layer, with a constant global bitrate and a dynamic bitrate ratio adjustment between layers. The proposed algorithm is evaluated on a UHD data set where enables on average a BD-BR gain of 4.25% compared to a fixed-ratio encoding.

关键词： HEVC SHVC UHD HD Rate-Control HD Bit rate High efficiency video coding BASE COURSE Scalability Operating Environment scalable video coding experimental conditions Video sequences computer algorithms Standing Orders

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Two Methods for the Identification of Uncertain Parameters of an Architectural Cable Net Geometry

Two Methods for the Identification of Uncertain Parameters o...

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IEEE Multi-Conference on Systems and Control

作者： Yvonne R. Sturz Manfred Morari Roy S. Smith Automatic Control Laboratory ETH Zurich

ISBN: (纸本)9781509007561

Recently, a control algorithm has been presented to control the geometry of a prestressed flexible cable net formwork, which is used for the construction of anticlastic thin concrete shell structures in architecture. The most important uncertainties in the model of the cable net are the parameters of unstressed lengths of its edges. As the control algorithm is model-based, its performance depends on the knowledge of these parameters. We present two methods for their identification, which are based on measurements of different configurations of the tensioned cable net. The first identification method uses a change of variables and a linear least squares approach. The second one is based on an optimization problem, which is solved in a distributed way by the Alternating Direction Method of Multipliers (ADMM) and is robust against the expected measurement noise. A numerical example demonstrates the performance of the identification methods.

关键词： computer algorithms Identification methods cable Nets geometry model uncertainty Noise measurement Least squares method concrete shell flexible cable

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Research on FCM and NHL Based High Order Mining Driven by Big Data

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MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-7页

作者： Peng, Zhen Peng, Jie Zhao, Wei Chen, Zhenguo Inst Sci & Technol Informat China Resource Sharing & Promot Ctr Beijing 100038 Peoples R China North China Inst Sci & Technol Sch Comp Beijing 101601 Peoples R China

In order to get the high order evaluation and correlation degree among big data with the characteristics of multidimension and multigranularity, an FCM and NHL based high order mining algorithm driven by big data is proposed, which is a kind of machine learning based on qualitative knowledge. The algorithmis applied in scientific and technical talent forecast. Driven by the big data of scientific research track of scientific and technical talents, the index system is designed and the big data is automatically acquired and processed. Accordingly, the high order evaluations in dimension level and target level can be inferred by the correlation weights mining. And the outstanding young talents in material field in 2014 have been actively recommended to review department for decision-making.

关键词： DATA mining DATA analysis computer algorithms DECISION making MACHINE learning

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Soylent: A Word Processor with a Crowd Inside

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COMMUNICATIONS OF THE ACM 2015年第8期58卷 85-94页

作者： Bernstein, Michael S. Little, Greg Miller, Robert C. Hartmann, Bjoern Ackerman, Mark S. Karger, David R. Crowell, David Panovich, Katrina Stanford Univ Stanford CA 94305 USA Univ Calif Berkeley Div Comp Sci Berkeley CA 94720 USA Univ Michigan Comp Sci & Engn Ann Arbor MI 48109 USA MIT CSAIL Cambridge MA USA Google Inc Mountain View CA USA

This paper introduces architectural and interaction patterns for integrating crowdsourced human contributions directly into user interfaces. We focus on writing and editing, complex endeavors that span many levels of conceptual and pragmatic activity. Authoring tools offer help with pragmatics, but for higher-level help, writers commonly turn to other people. We thus present Soylent, a word processing interface that enables writers to call on Mechanical Turk workers to shorten, proofread, and otherwise edit parts of their documents on demand. To improve worker quality, we introduce the Find-Fix-Verify crowd programming pattern, which splits tasks into a series of generation and review stages. Evaluation studies demonstrate the feasibility of crowdsourced editing and investigate questions of reliability, cost, wait time, and work time for edits.

关键词： Crowdsourcing computer architecture User interfaces (computer systems) Human-machine systems computer programming Electronic data processing computer algorithms

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Ontology population as algebraic information system processing based on multi-agent natural language text analysis algorithms

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PROGRAMMING AND computer SOFTWARE 2015年第3期41卷 140-148页

作者： Garanina, N. O. Sidorova, E. A. Russian Acad Sci AP Ershov Inst Informat Syst Siberian Div Novosibirsk 630090 Russia

The paper presents an approach to ontology population as operations with Scott information system. The deducibility relation in the ontology population information system corresponds to rules of input data processing and ontology population. To implement an ontology population process, we suggest a multi-agent approach based on natural language semantic analysis. In the proposed multi-agent model, agents of the following two types interact: information agents corresponding to meaningful units of the information being retrieved and rule agents implementing population rules of the given ontology based on the semantic-syntactic model of the language.

关键词： INFORMATION processing INFORMATION storage & retrieval systems MULTIAGENT systems NATURAL language processing (computer science) computer algorithms ONTOLOGY

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A Hybrid Backtracking Search Optimization Algorithm with Differential Evolution

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MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-16页

作者： Wang, Lijin Zhong, Yiwen Yin, Yilong Zhao, Wenting Wang, Binqing Xu, Yulong Fujian Agr & Forestry Univ Coll Comp & Informat Sci Fuzhou 350002 Peoples R China Shandong Univ Sch Comp Sci & Technol Jinan 250101 Peoples R China Shandong Univ Finance & Econ Sch Comp Sci & Technol Jinan 250014 Peoples R China

The backtracking search optimization algorithm (BSA) is a new nature-inspired method which possesses a memory to take advantage of experiences gained from previous generation to guide the population to the global optimum. BSA is capable of solving multimodal problems, but it slowly converges and poorly exploits solution. The differential evolution (DE) algorithm is a robust evolutionary algorithm and has a fast convergence speed in the case of exploitive mutation strategies that utilize the information of the best solution found so far. In this paper, we propose a hybrid backtracking search optimization algorithm with differential evolution, called HBD. In HBD, DE with exploitive strategy is used to accelerate the convergence by optimizing one worse individual according to its probability at each iteration process. A suit of 28 benchmark functions are employed to verify the performance of HBD, and the results show the improvement in effectiveness and efficiency of hybridization of BSA and DE.

关键词： DIFFERENTIAL evolution (computer science) computer algorithms SEARCH algorithms EVOLUTIONARY algorithms PROBABILITY theory PROBLEM solving

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A Load Balancing Scheme Using Federate Migration Based on Virtual Machines for Cloud Simulations

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MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-11页

作者： Song, Xiao Ma, Yaofei Teng, Da Beihang Univ Sch Automat Sci Sci & Technol Aircraft Control Lab Beijing 100191 Peoples R China

A maturing and promising technology, Cloud computing can benefit large-scale simulations by providing on-demand, anywhere simulation services to users. In order to enable multitask and multiuser simulation systems with Cloud computing, Cloud simulation platform (CSP) was proposed and developed. To use key techniques of Cloud computing such as virtualization to promote the running efficiency of large-scale military HLA systems, this paper proposes a new type of federate container, virtual machine (VM), and its dynamic migration algorithm considering both computation and communication cost. Experiments show that the migration scheme effectively improves the running efficiency of HLA system when the distributed system is not saturated.

关键词： LOADS (Mechanics) VIRTUAL machine systems SIMULATION methods & models CLOUD computing computer algorithms

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A Decomposition-Based Two-Stage Optimization Algorithm for Single Machine Scheduling Problems with Deteriorating Jobs

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MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-8页

作者： Liu, Yueyue Zhang, Rui Wang, Miaomiao Zhu, Xiaoxi Nanchang Univ Sch Econ & Management Nanchang 330031 Peoples R China

This paper studies a production scheduling problem with deteriorating jobs, which frequently arises in contemporary manufacturing environments. The objective is to find an optimal sequence of the set of jobs to minimize the total weighted tardiness, which is an indicator of service quality. The problem belongs to the class of NP-hard. When the number of jobs increases, the computational time required by an optimization algorithm to solve the problem will increase exponentially. To tackle large-scale problems efficiently, a two-stage method is presented in this paper. We partition the set of jobs into a few subsets by applying a neural network approach and thereby transform the large-scale problem into a series of small-scale problems. Then, we employ an improved metaheuristic algorithm (called GTS) which combines genetic algorithm with tabu search to find the solution for each subproblem. Finally, we integrate the obtained sequences for each subset of jobs and produce the final complete solution by enumeration. A fair comparison has been made between the two-stage method and the GTS without decomposition, and the experimental results show that the solution quality of the two-stage method is much better than that of GTS for large-scale problems.

关键词： DECOMPOSITION (Mathematics) computer algorithms MACHINE theory PRODUCTION scheduling NP-hard problems

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Multiobjective Particle Swarm Optimization Based on PAM and Uniform Design

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MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-17页

作者： Zhu, Xiaoshu Zhang, Jie Feng, Junhong Yulin Normal Univ Guangxi Univ Key Lab Complex Syst Optimizat & Big Data Proc Sch Comp Sci & Engn Yulin 537000 Peoples R China

In MOPSO (multiobjective particle swarm optimization), to maintain or increase the diversity of the swarm and help an algorithm to jump out of the local optimal solution, PAM (Partitioning Around Medoid) clustering algorithm and uniform design are respectively introduced to maintain the diversity of Pareto optimal solutions and the uniformity of the selected Pareto optimal solutions. In this paper, a novel algorithm, the multiobjective particle swarm optimization based on PAM and uniform design, is proposed. The differences between the proposed algorithm and the others lie in that PAM and uniform design are firstly introduced to MOPSO. The experimental results performing on several test problems illustrate that the proposed algorithm is efficient.

关键词： PARTICLE swarm optimization MULTIPLE criteria decision making computer algorithms PARETO analysis computer programming

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A Novel Approach to a Mobile Robot via Multiple Human Body Postures

A Novel Approach to a Mobile Robot via Multiple Human Body P...

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World Congress on Intelligent Control and Automation

作者： Dajun Zhou Fei Chao Zuyuan Zhu Chih-Min Lin Changle Zhou Cognitive Science Department Fujian Province Key Lab of Machine Intelligence and Robotics School of Information Science and Engineering Xiamen University

ISBN: (纸本)9781467384155

This paper focuses on applying human postures and face tracking technologies to design an autonomous patrol vehicle control system, which contains a wireless video surveillance ability. The entire system includes the following several parts: (1) Obtaining the skeleton joints based on the Kinect skeleton tracking: the angles and distances between each human arm's joint are calculated to be the input of an artificial neural networks. (2) Changing the vehicle's gear box: the dynamic gesture recognition is built by using the artificial neural network and a finite state machine. (3) Controlling the vehicle speed, the speed is controlled by a fuzzy control algorithm. (4) Controlling of a motorized camera: the Kinect face tracking function is applied to detect a human's fact direction, so that, the motorized camera's rotation is controlled by the direction. This project expands the application range of intelligent mobile robots and improves the robotic autonomous ability to deal with complex environments.

关键词： Mobile robots body position Artificial neural networks Gesture recognition face tracking game player Human Posture Angle computer algorithms vehicle Human Body state machines Cameras Skeletons bone structure

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